Emile van Krieken

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Frank van HarmelenDept. of Computer Science, Vrije Universiteit AmsterdamVerified email at vu.nl
Erman AcarInstitute of Logic, Language and Computation & Informatics Institute, University of AmsterdamVerified email at uva.nl
Thiviyan ThanapalasingamIntelligent Data Engineering Lab (INDElab) at the University of AmsterdamVerified email at uva.nl
Jakub M. TomczakAssociate professor at Eindhoven University of TechnologyVerified email at tue.nl
Annette ten TeijeComputer Science, Vrije Universiteit AmsterdamVerified email at cs.vu.nl
Antonio VergariReader (Associate Professor), University of Edinburgh, UKVerified email at ed.ac.uk
Pasquale MinerviniUniversity of Edinburgh, Miniml.AI, ELLIS ScholarVerified email at ed.ac.uk
Emanuele MarconatoUniversity of Pisa and University of TrentoVerified email at unitn.it
Stefano TesoSenior Assistant Professor, University of TrentoVerified email at unitn.it
Andrea PasseriniAssociate Professor, University of TrentoVerified email at disi.unitn.it
Samuele BortolottiPhD Student, University of TrentoVerified email at unitn.it
Peter BloemVrije Universiteit AmsterdamVerified email at peterbloem.nl
Alessandro DanieleFondazione Bruno KesslerVerified email at fbk.eu
Luciano SerafiniHead of Data and Knowledge Management Research Unit, Fondazione Bruno Kessler, Trento, ItalyVerified email at fbk.eu
Edoardo M. PontiUniversity of Edinburgh / NVIDIAVerified email at ed.ac.uk
Taraneh YounesianPhD student at VU AmsterdamVerified email at vu.nl
Eleonora GiunchigliaImperial College LondonVerified email at cs.ox.ac.uk
Robin ManhaeveDTAI, KU LeuvenVerified email at cs.kuleuven.be
Samy BadreddineSony AIVerified email at sony.com
Daniel DazaAmsterdam UMCVerified email at vu.nl

Emile van Krieken

Research Associate, University of Edinburgh

Verified email at ed.ac.uk - Homepage

Neurosymbolic AI Machine Learning Optimization Generative Models


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Analyzing differentiable fuzzy logic operators E van Krieken, E Acar, F van Harmelen Artificial Intelligence 302, 103602, 2022	164	2022
Prompting as probing: Using language models for knowledge base construction D Alivanistos, SB Santamaría, M Cochez, JC Kalo, E van Krieken, ... LM-KBC Challenge 2022, 2022	51	2022
Analyzing Differentiable Fuzzy Implications E van Krieken, E Acar, F van Harmelen KR 2020, 893–903, 2020	43	2020
A-nesi: A scalable approximate method for probabilistic neurosymbolic inference E van Krieken, T Thanapalasingam, J Tomczak, F Van Harmelen, ... NeurIPS 2023 36, 24586-24609, 2023	36	2023
Semi-Supervised Learning using Differentiable Reasoning E van Krieken, E Acar, F van Harmelen IFCoLog Journal of Logic and its Applications 6 (4), 633-653, 2019	24	2019
Are We Done with MMLU? AP Gema, JOJ Leang, G Hong, A Devoto, ACM Mancino, R Saxena, X He, ... arXiv preprint arXiv:2406.04127, 2024	23*	2024
Storchastic: A framework for general stochastic automatic differentiation E van Krieken, J Tomczak, A Ten Teije NeurIPS 2021 34, 7574-7587, 2021	20	2021
Refining neural network predictions using background knowledge A Daniele, E van Krieken, L Serafini, F van Harmelen Machine Learning 112 (9), 3293-3331, 2023	11	2023
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts E Marconato, S Bortolotti, E van Krieken*, A Vergari, A Passerini, S Teso UAI 2024 (Spotlight), 2024	8	2024
Grapes: Learning to sample graphs for scalable graph neural networks T Younesian, D Daza, E van Krieken, T Thanapalasingam, P Bloem arXiv preprint arXiv:2310.03399, 2023	4	2023
On the Independence Assumption in Neurosymbolic Learning E van Krieken, P Minervini, EM Ponti, A Vergari ICML 2024, 2024	3	2024
Benefits of social learning in physical robots J Heinerman, B Bussmann, R Groenendijk, E Van Krieken, J Slik, A Tezza, ... 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 851-858, 2018	2	2018
A neuro-symbolic benchmark suite for concept quality and reasoning shortcuts S Bortolotti, E Marconato, T Carraro, P Morettin, E van Krieken, A Vergari, ... NeurIPS 2024, 1-44, 2024	1	2024
Optimisation in Neurosymbolic Learning Systems E van Krieken arXiv preprint arXiv:2401.10819, 2024	1	2024
IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation T Thanapalasingam, E van Krieken, P Bloem, P Groth arXiv preprint arXiv:2307.06698, 2023	1	2023
Analysis of Measure-Valued Derivatives in a Reinforcement Learning Actor-Critic Framework K Van Den Houten, E Van Krieken, B Heidergott 2022 Winter Simulation Conference (WSC), 2736-2747, 2022	1	2022
Mixtures of In-Context Learners G Hong, E van Krieken, E Ponti, N Malkin, P Minervini arXiv preprint arXiv:2411.02830, 2024		2024
ULLER: A Unified Language for Learning and Reasoning E van Krieken, S Badreddine, R Manhaeve, E Giunchiglia NeSy 2024 (Spotlight), 219-239, 2024		2024
Differentiable Fuzzy Logics E van Krieken Vrije Universiteit, 2019		2019

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